Triple

T13152335
Position Surface form Disambiguated ID Type / Status
Subject Minden, Germany E312496 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object MI
MI is the vehicle registration code used on license plates for vehicles registered in Minden, a town in Germany.
 E1025306 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: MI | Statement: [Minden, Germany, vehicleRegistrationCode, MI]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MI
Context triple: [Minden, Germany, vehicleRegistrationCode, MI]
  • A. MI
    MI is the official two-letter United States Postal Service abbreviation for the state of Michigan.
  • B. MI
    MI is the commonly used abbreviation for the Mumbai Indians, a prominent franchise cricket team in the Indian Premier League.
  • C. Mi
    Mi was the ancestral clan name of the royal house of the ancient Chinese state of Chu, to which King Zhuang of Chu belonged.
  • D. Mi
    Mi is a sub-brand of Xiaomi used primarily for its line of consumer electronics and smart devices, including smartphones, TVs, and streaming boxes.
  • E. Mil
    Mil is a Russian surname most famously associated with Mikhail Mil, the pioneering Soviet aerospace engineer and helicopter designer.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: MI
Triple: [Minden, Germany, vehicleRegistrationCode, MI]
Generated description
MI is the vehicle registration code used on license plates for vehicles registered in Minden, a town in Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MI
Target entity description: MI is the vehicle registration code used on license plates for vehicles registered in Minden, a town in Germany.
  • A. MI
    MI is the official two-letter United States Postal Service abbreviation for the state of Michigan.
  • B. MI
    MI is the commonly used abbreviation for the Mumbai Indians, a prominent franchise cricket team in the Indian Premier League.
  • C. Mi
    Mi was the ancestral clan name of the royal house of the ancient Chinese state of Chu, to which King Zhuang of Chu belonged.
  • D. Mi
    Mi is a sub-brand of Xiaomi used primarily for its line of consumer electronics and smart devices, including smartphones, TVs, and streaming boxes.
  • E. Mil
    Mil is a Russian surname most famously associated with Mikhail Mil, the pioneering Soviet aerospace engineer and helicopter designer.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d806aabde48190899e13e41659cae5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98bd317e0819086e383f8e4583630 completed April 10, 2026, 11:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6eaeca00c8190aa5645d1084c7d60 completed May 3, 2026, 6:27 a.m.
NEDg Description generation batch_69f6f17376c88190b08a4f2f5967b57c completed May 3, 2026, 6:55 a.m.
NED2 Entity disambiguation (via description) batch_69f6f1e5bc888190a0a82f45922de104 completed May 3, 2026, 6:57 a.m.
Created at: April 9, 2026, 9:11 p.m.